bioRxivGenomicsPreprint
Twenty-five new microsporidian genomes: Insights into ploidy, reproduction, and the group's pangenome
Amjad KhalafiD, Diégo AyalaiD, Nathan W. BaileyiD, Lia BoteiD, Ore FrancisiD, Kamil S. JaroňiD, Erna KingiD, Mara LawniczakiD, Peter G. Mullin, Kerstin Powers, Thomas O. Powers, Camilla Santos, Mark BlaxteriD
Abstract
Microsporidia are single-celled, obligately intracellular eukaryotic parasites of growing importance. Many aspects of their biology remain enigmatic, partly because of difficulties in sampling, culturing, and experimentally manipulating them. Here, we continue efforts to generate microsporidian genomes from serendipitously infected organisms sequenced for biodiversity genomics initiatives, such as the Darwin Tree of Life Project. We present 25 new microsporidian genomes: 14 biologically complete, including several at (near-)chromosome level, and 11 partial. Using RNA-seq data for three published genomes we identify Prokka as a suitable ab initio annotation approach for Microsporidia. Consistently annotating all available genomes, we investigate gene-content diversity across microsporidian clades. We find that the microsporidian pangenome exhibits extreme diversity, and that current genomic data substantially undersample the group's proteome space. Neither GC content nor genome span consistently explains orthogroup number across lineages, suggesting different evolutionary pressures. We find few one-to-one orthogroups in Microsporidia, as well as few orthogroups that are both lineage-specific and conserved across most species within a given lineage. Finally, Hi-C data confirm that tetraploid Amblyosporida microsporidia occur as two equivalent diploid units. In contrast, one Enterocytozoonida tetraploid genome suggests that all four genome copies occur within a single nucleus (a 'monokaryon'), confirming a previous proposal.
- assay: whole-genome sequencing
- research focus: database / resource
- research focus: gene regulatory network inference
- research focus: variant calling
- approach: statistical model
- approach: experimental assay
- Citations
- 0
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